Nathaniel Joseph Pastika
Baylor University
https://lpc.fnal.gov/fellows/2019/Nathaniel_Joseph_Pastika.shtml
I will be working on advanced methods of top tagging employing machine learning techniques. In particular, I will continue to develop novel ways to apply deep neural networks to the problem of identifying top quarks in a wide array of event topoligies and over a large range of top transverse momenta. These top tagging techniques will then be applied in the LPC centered search looking specifically for third generation sparticles whose final states contain top and bottom quarks. The application of the top tagging algorithm to these signal topoligies greatly improves the sensitivity of these searches by removing unwanted backgrounds dominated by light quark/gluon initiated jets such as Z+jets events. In addition to analysis work, I also plan to contribute to the ongoing phase 1 and 2 calorimeter upgrade effort.
I have been a member of the CMS Collaboration since 2011 with experience in exotica and SUSY searches as well as extensive hardware experience working on the CMS hadronic calorimeter. I have been a member of the LPC centered top squark search for several years and this lead to my current work to improve the existing top tagging algorithms, particularly in application to SUSY inspired search signatures. I also am co-leader of the SUSY Heavy-Object-Tagging working group. In the past years, I have also been leading hardware testing and integration for the HE phase 1 upgrade effort at the LPC including the 2015 test beam effort and the full quantity control of the front-end readout cards for HE.